The raw data rate of video signals originating from video sources such as cameras is typically too high for practical transmission over operator and broadcast networks. Thus, significant efforts have been underway for decades to reduce the amount of bandwidth required to transport, store, and broadcast video signals, while retaining high visual quality. Practical video encoders (often referred to as “codecs,” for coder/decoder) are inherently lossy. Ideally, these video encoders discard information typically not visible to the human eye. However, in operation, such a lossy processes introduce unwanted artifacts into the original stream, typically referred to as video encoding artifacts.
Broadcasting, telecommunications or cable operators, video and/or film production facilities, etc. are generally forced to make tradeoffs between video encoding artifacts and bandwidth requirements of the encoded signal. Finding a suitable encoding rate, while keeping visible artifacts to a minimum for most viewers is often a challenge. Traditionally, trained human observers, skilled in the art of recognizing various forms of video impairments, are required to visually determine encoding artifacts. The ability to discern, recognize, and point out video encoding artifacts can be learned over a period of time. Untrained viewers often struggle in recognizing specific types of artifacts.
Hence, there is a need for more robust and scalable solutions for implementing video encoding and decoding, and, more particularly, to methods, systems, and apparatuses for implementing detection and visual enhancement of video encoding artifacts.